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MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures

dc.contributor.authorVázquez, Miguel
dc.contributor.authorNogales Cadenas, Rubén
dc.contributor.authorArroyo, Javier
dc.contributor.authorBotias, Pedro
dc.contributor.authorGarcía, Raúl
dc.contributor.authorTirado Fernández, José Francisco
dc.contributor.authorCarazo, José M.
dc.contributor.authorPascual Montano, Alberto
dc.contributor.authorCarmona Saez, Pedro
dc.date.accessioned2023-06-20T04:05:18Z
dc.date.available2023-06-20T04:05:18Z
dc.date.issued2010-07
dc.description© The Author(s) 2010. Published by Oxford University Press. Spanish grants (BIO2007-67150-C03-02, S-Gen-0166/2006, TIN2005-5619, and PS-010000-2008-1). Funding for open access charge: European Union (project FP7-HEALTH-F4-2008-202047); Ministerio de Ciencia e Innovacion (projects BIO2007-67150-C03-02, PS-010000-2008-1); Comunidad de Madrid (S-Gen-0166/2006).
dc.description.abstractMedical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.
dc.description.departmentSección Deptal. de Arquitectura de Computadores y Automática (Físicas)
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipUnión Europea. FP7
dc.description.sponsorshipMinisterio de Ciencia e Innovacion (MICIN)
dc.description.sponsorshipComunidad de Madrid
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/35614
dc.identifier.doi10.1093/nar/gkq476
dc.identifier.issn0305-1048
dc.identifier.officialurlhttp://dx.doi.org/10.1093/nar/gkq476
dc.identifier.relatedurlhttp://nar.oxfordjournals.org/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/44897
dc.journal.titleNucleic acids research
dc.language.isoeng
dc.page.finalW232
dc.page.initialW228
dc.publisherOxford Univ Press
dc.relation.projectIDFP7-HEALTH-F4-2008 (202047)
dc.relation.projectIDBIO2007-67150-C03-02
dc.relation.projectIDPS-010000-2008-1
dc.relation.projectIDS-Gen-0166/2006
dc.relation.projectIDTIN2005-5619
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.cdu004
dc.subject.keywordCell wall stress
dc.subject.keywordProfiles
dc.subject.keywordPathways
dc.subject.keywordDiscovery
dc.subject.keywordPowerful
dc.subject.ucmInformática (Informática)
dc.subject.unesco1203.17 Informática
dc.titleMARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures
dc.typejournal article
dc.volume.number38
dcterms.references1. Barrett,T., Troup,D.B., Wilhite,S.E., Ledoux,P., Rudnev,D., Evangelista,C., Kim,I.F., Soboleva,A., Tomashevsky,M., Marshall,K.A. et al. (2009) NCBI GEO: archive for high-throughput functional genomic data. Nucleic Acids Res., 37, D885–D890. 2. Lamb,J., Crawford,E.D., Peck,D., Modell,J.W., Blat,I.C., Wrobel,M.J., Lerner,J., Brunet,J.P., Subramanian,A., Ross,K.N. et al. (2006) The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science, 313, 1929–1935. 3. Hughes,T.R., Marton,M.J., Jones,A.R., Roberts,C.J., Stoughton,R., Armour,C.D., Bennett,H.A., Coffey,E., Dai,H., He,Y.D. et al. (2000) Functional discovery via a compendium of expression profiles. Cell, 102, 109–126. 4. Rhodes,D.R., Kalyana-Sundaram,S., Mahavisno,V., Varambally,R., Yu,J., Briggs,B.B., Barrette,T.R., Anstet,M.J., Kincead-Beal,C., Kulkarni,P. et al. (2007) Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia, 9, 166–180. 5. Subramanian,A., Tamayo,P., Mootha,V.K., Mukherjee,S., Ebert,B.L., Gillette,M.A., Paulovich,A., Pomeroy,S.L., Golub,T.R., Lander,E.S. et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA, 102, 15545–15550. 6. Newman,J.C. and Weiner,A.M. (2005) L2L: a simple tool for discovering the hidden significance in microarray expression data. Genome Biol., 6, R81. 7. Yi,Y., Li,C., Miller,C. and George,A.L. Jr (2007) Strategy for encoding and comparison of gene expression signatures. Genome Biol., 8, R133. 8. Sean,D. and Meltzer,P.S. (2007) GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics, 23, 1846. 9. Benjamini,Y. and Hochberg,Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Stat. Soc. B, 289–300. 10. Efron,B. and Tibshirani,R. (2007) On testing the significance of sets of genes. Ann. Appl. Stat., 1, 107–129. 11. Breitling,R., Armengaud,P., Amtmann,A. and Herzyk,P. (2004) Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments. FEBS Lett., 573, 83–92. 12. Garcia,R., Rodriguez-Pena,J.M., Bermejo,C., Nombela,C. and Arroyo,J. (2009) The high osmotic response and cell wall integrity pathways cooperate to regulate transcriptional responses to zymolyase-induced cell wall stress in Saccharomyces cerevisiae. J. Biol. Chem., 284, 10901–10911. 13. Arroyo,J., Bermejo,C., Garcia,R. and Rodriguez-Pena,J. (2009) Genomics in the detection of damage in microbial systems: cell wall stress in yeast. Clin. Microbiol. Infect., 15, 44–46. 14. Roberts,C.J., Nelson,B., Marton,M.J., Stoughton,R., Meyer,M.R., Bennett,H.A., He,Y.D., Dai,H., Walker,W.L., Hughes,T.R. et al. (2000) Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles. Science, 287, 873–880.
dspace.entity.typePublication
relation.isAuthorOfPublication1356616c-9e69-4852-8415-62fd0b8e7cfc
relation.isAuthorOfPublication.latestForDiscovery1356616c-9e69-4852-8415-62fd0b8e7cfc

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